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Introduction: Studies of lip prints and palatal rugae, dates back to late 19(th) and early 20(th) centuries and since then, various methods of classification and analysis were introduced, however systematic recording and analysis of data is still need to improve further, to arrive at flawless and meaningful conclusions. Moreover, the awareness among dental personnel regarding the practical knowledge of cheiloscopy and palatoscopy is ambiguous. So, efforts have been made to introduce training module to improve the education of cheiloscopy and palatoscopy for dental students.
Aims And Objective: 1. To prepare training module for cheiloscopy and palatoscopy. 2. To assess the efficacy of designed training module.
Materials And Methods: Training module was used to train the dental students. Random matching of lip and palatal rugae patterns was carried out by dental students before and after training. Pre- and post-training matched results were then compared. Intraobserver variability assessed by comparing first and second assessment of lip print and palatal rugae patterns.
Results: It was inferred statistically that training module had improved the ability to identify individuals based on lip prints and palatal rugae, with insignificant intraobserver variation.
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http://dx.doi.org/10.4103/0975-1475.127768 | DOI Listing |
Biomed Phys Eng Express
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Siemens Healthineers AG, 810 Innovation Dr, Knoxville, Tennessee, 37932-2562, UNITED STATES.
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View Article and Find Full Text PDFNeural Netw
September 2025
School of Computer Science, South China Normal University, Guangzhou, 510631, Guangdong, China; School of Artificial Intelligence, South China Normal University, Foshan, 528225, Guangdong, China. Electronic address:
Data-Free Knowledge Distillation (DFKD) have achieved significant breakthroughs, enabling the effective transfer of knowledge from teacher neural networks to student neural networks without reliance on original data. However, a significant challenge faced by existing methods that attempt to generate samples from random noise is that the noise lacks meaningful information, such as class-specific semantic information. Consequently, the absence of meaningful information makes it difficult for the generator to map this noise to the ground-truth data distribution, resulting in the generation of low-quality training samples.
View Article and Find Full Text PDFJ Am Coll Health
September 2025
Hubbard School of Journalism and Mass Communication, University of Minnesota, Minneapolis, Minnesota, USA.
: An evolving THC product marketplace is diffusing through college campuses. It is essential to understand college students' THC knowledge, attitudes, practices and product packaging perceptions to identify campus health education and messaging strategies. : Participants were 30 undergraduate college students at a large-midwestern, public university.
View Article and Find Full Text PDFPLoS Negl Trop Dis
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Universitat Oberta de Catalunya, Barcelona, Spain.
Background: Originally adapted from a paper-based guide for skin-related neglected tropical diseases (NTDs), version 3.0.0 of the World Health Organization (WHO) SkinNTDs app aims to strengthen disease surveillance and frontline health worker capacity in NTD-endemic settings.
View Article and Find Full Text PDFAdv Physiol Educ
September 2025
Division of Epidemiology and Biostatistics, St. John's Medical College, Bangalore, Karnataka, India.
The amphibian dissection for medical students was halted by the restrictions imposed by the National regulatory guidelines, prompting medical curricula to revise and innovate instructional methods. Hence there is a critical need for potential innovative solutions to enhance students' understanding of physiological concepts. Therefore, this study aimed (a) to evaluate the gain in knowledge and retention with computer assisted simulation (CAS) vs traditional (TT) teaching learning strategies in first year medical and paramedical students, and (b) to obtain students' and faculty feedback about strengths and limitations of both strategies.
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